mirror of
https://gitee.com/milvus-io/milvus.git
synced 2025-12-07 01:28:27 +08:00
388d56fdc7
### Is there an existing issue for this? - [x] I have searched the existing issues --- Please see: https://github.com/milvus-io/milvus/issues/44593 for the background This PR makes https://github.com/milvus-io/milvus/pull/44638 redundant, which can be closed. The PR comments for the original implementation suggested an alternative and a better approach, this new PR has that implementation. --- This PR - Adds an optional `minimum_should_match` argument to `text_match(...)` and wires it through the parser, planner/visitor, index bindings, and client-level tests/examples so full-text queries can require a minimum number of tokens to match. Motivation - Provide a way to require an expression to match a minimum number of tokens in lexical search. What changed - Parser / grammar - Added grammar rule and token: `MINIMUM_SHOULD_MATCH` and `textMatchOption` in `internal/parser/planparserv2/Plan.g4`. - Regenerated parser outputs: `internal/parser/planparserv2/generated/*` (parser, lexer, visitor, etc.) to support the new rule. - Planner / visitor - `parser_visitor.go`: parse and validate the `minimum_should_match` integer; propagate as an extra value on the `TextMatch` expression so downstream components receive it. - Added `VisitTextMatchOption` visitor method handling. - Client (Golang) - Added a unit test to verify `text_match(..., minimum_should_match=...)` appears in the generated DSL and is accepted by client code: `client/milvusclient/read_test.go` (new test coverage). - Added an integration-style test for the feature to the go-client testcase suite: `tests/go_client/testcases/full_text_search_test.go` (exercise min=1, min=3, large min). - Added an example demonstrating `text_match` usage: `client/milvusclient/read_example_test.go` (example name conforms to godoc mapping). - Engine / index - Updated C++ index interface: `TextMatchIndex::MatchQuery` - Added/updated unit tests for the index behavior: `internal/core/src/index/TextMatchIndexTest.cpp`. - Tantivy binding - Added `match_query_with_minimum` implementation and unit tests to `internal/core/thirdparty/tantivy/tantivy-binding/src/index_reader_text.rs` that construct boolean queries with minimum required clauses. Behavioral / compatibility notes - This adds an optional argument to `text_match` only; default behavior (no `minimum_should_match`) is unchanged. - Internal API change: `TextMatchIndex::MatchQuery` signature changed (internal component). Callers in the repo were updated accordingly. - Parser changes required regenerating ANTLR outputs Tests and verification - New/updated tests: - Go client unit test: `client/milvusclient/read_test.go` (mocked Search request asserts DSL contains `minimum_should_match=2`). - Go e2e-style test: `tests/go_client/testcases/full_text_search_test.go` (exercises min=1, 3 and a large min). - C++ unit tests for index behavior: `internal/core/src/index/TextMatchIndexTest.cpp`. - Rust binding unit tests for `match_query_with_minimum`. - Local verification commands to run: - Go client tests: `cd client && go test ./milvusclient -run ^$` (client package) - Go testcases: `cd tests/go_client && go test ./testcases -run TestTextMatchMinimumShouldMatch` (requires a running Milvus instance) - C++ unit tests / build: run core build/test per repo instructions (the change touches core index code). - Rust binding tests: `cd internal/core/thirdparty/tantivy/tantivy-binding && cargo test` (if developing locally). --------- Signed-off-by: Amit Kumar <amit.kumar@reddit.com> Co-authored-by: Amit Kumar <amit.kumar@reddit.com>
382 lines
16 KiB
Go
382 lines
16 KiB
Go
package testcases
|
|
|
|
import (
|
|
"fmt"
|
|
"testing"
|
|
"time"
|
|
|
|
"github.com/stretchr/testify/require"
|
|
|
|
"github.com/milvus-io/milvus/client/v2/entity"
|
|
"github.com/milvus-io/milvus/client/v2/index"
|
|
"github.com/milvus-io/milvus/client/v2/milvusclient"
|
|
"github.com/milvus-io/milvus/tests/go_client/common"
|
|
hp "github.com/milvus-io/milvus/tests/go_client/testcases/helper"
|
|
)
|
|
|
|
func TestFullTextSearchDefault(t *testing.T) {
|
|
ctx := hp.CreateContext(t, time.Second*common.DefaultTimeout)
|
|
mc := hp.CreateDefaultMilvusClient(ctx, t)
|
|
|
|
// create -> insert -> flush -> index -> load
|
|
analyzerParams := map[string]any{"tokenizer": "standard"}
|
|
fieldsOption := hp.TNewFieldsOption().TWithAnalyzerParams(analyzerParams)
|
|
function := hp.TNewBM25Function(common.DefaultTextFieldName, common.DefaultTextSparseVecFieldName)
|
|
schemaOption := hp.TNewSchemaOption().TWithFunction(function)
|
|
prepare, schema := hp.CollPrepare.CreateCollection(ctx, t, mc, hp.NewCreateCollectionParams(hp.FullTextSearch), fieldsOption, schemaOption)
|
|
insertOption := hp.TNewDataOption().TWithTextLang(common.DefaultTextLang)
|
|
prepare.InsertData(ctx, t, mc, hp.NewInsertParams(schema), insertOption)
|
|
prepare.FlushData(ctx, t, mc, schema.CollectionName)
|
|
|
|
indexparams := hp.TNewIndexParams(schema).TWithFieldIndex(map[string]index.Index{common.DefaultTextSparseVecFieldName: index.NewSparseInvertedIndex(entity.BM25, 0.1)})
|
|
prepare.CreateIndex(ctx, t, mc, indexparams)
|
|
prepare.Load(ctx, t, mc, hp.NewLoadParams(schema.CollectionName))
|
|
|
|
// search
|
|
queries := hp.GenFullTextQuery(common.DefaultNq, common.DefaultTextLang)
|
|
vectors := make([]entity.Vector, 0, len(queries))
|
|
for _, query := range queries {
|
|
vectors = append(vectors, entity.Text(query))
|
|
}
|
|
resSearch, err := mc.Search(ctx, milvusclient.NewSearchOption(schema.CollectionName, common.DefaultLimit, vectors).WithConsistencyLevel(entity.ClStrong))
|
|
common.CheckErr(t, err, true)
|
|
common.CheckSearchResult(t, resSearch, common.DefaultNq, common.DefaultLimit)
|
|
}
|
|
|
|
// TestSearchFullTextBase tests basic full text search functionality with different languages
|
|
func TestSearchFullTextWithDiffLang(t *testing.T) {
|
|
ctx := hp.CreateContext(t, time.Second*common.DefaultTimeout)
|
|
mc := hp.CreateDefaultMilvusClient(ctx, t)
|
|
|
|
// Test cases for different languages and analyzers
|
|
testCases := []struct {
|
|
name string
|
|
language string
|
|
analyzer string
|
|
query string
|
|
numRows int
|
|
topK int
|
|
}{
|
|
{
|
|
name: "English_Standard",
|
|
language: "english",
|
|
analyzer: "standard",
|
|
query: "what is information retrieval and its applications?",
|
|
numRows: 3000,
|
|
topK: 10,
|
|
},
|
|
{
|
|
name: "Chinese_Jieba",
|
|
language: "chinese",
|
|
analyzer: "jieba",
|
|
query: "信息检索的应用",
|
|
numRows: 3000,
|
|
topK: 10,
|
|
},
|
|
}
|
|
|
|
for _, tc := range testCases {
|
|
t.Run(tc.name, func(t *testing.T) {
|
|
analyzerParams := map[string]any{"tokenizer": tc.analyzer}
|
|
fieldsOption := hp.TNewFieldsOption().TWithAnalyzerParams(analyzerParams)
|
|
function := hp.TNewBM25Function(common.DefaultTextFieldName, common.DefaultTextSparseVecFieldName)
|
|
schemaOption := hp.TNewSchemaOption().TWithFunction(function)
|
|
prepare, schema := hp.CollPrepare.CreateCollection(ctx, t, mc, hp.NewCreateCollectionParams(hp.FullTextSearch), fieldsOption, schemaOption)
|
|
insertOption := hp.TNewDataOption().TWithTextLang(tc.language).TWithNb(tc.numRows)
|
|
prepare.InsertData(ctx, t, mc, hp.NewInsertParams(schema), insertOption)
|
|
prepare.FlushData(ctx, t, mc, schema.CollectionName)
|
|
|
|
indexparams := hp.TNewIndexParams(schema).TWithFieldIndex(map[string]index.Index{common.DefaultTextSparseVecFieldName: index.NewSparseInvertedIndex(entity.BM25, 0.1)})
|
|
prepare.CreateIndex(ctx, t, mc, indexparams)
|
|
prepare.Load(ctx, t, mc, hp.NewLoadParams(schema.CollectionName))
|
|
|
|
// search
|
|
queries := []string{tc.query}
|
|
vectors := make([]entity.Vector, 0, len(queries))
|
|
for _, query := range queries {
|
|
vectors = append(vectors, entity.Text(query))
|
|
}
|
|
resSearch, err := mc.Search(ctx, milvusclient.NewSearchOption(schema.CollectionName, tc.topK, vectors).WithConsistencyLevel(entity.ClStrong))
|
|
common.CheckErr(t, err, true)
|
|
common.CheckSearchResult(t, resSearch, len(queries), tc.topK)
|
|
})
|
|
}
|
|
}
|
|
|
|
// TestSearchFullTextWithDynamicField tests full text search with dynamic field enabled
|
|
func TestSearchFullTextWithDynamicField(t *testing.T) {
|
|
ctx := hp.CreateContext(t, time.Second*common.DefaultTimeout)
|
|
mc := hp.CreateDefaultMilvusClient(ctx, t)
|
|
// Test cases for different languages and analyzers
|
|
testCases := []struct {
|
|
name string
|
|
language string
|
|
analyzer string
|
|
query string
|
|
numRows int
|
|
topK int
|
|
}{
|
|
{
|
|
name: "English_Standard",
|
|
language: "english",
|
|
analyzer: "standard",
|
|
query: "what is information retrieval and its applications?",
|
|
numRows: 1000,
|
|
topK: 5,
|
|
},
|
|
{
|
|
name: "Chinese_Jieba",
|
|
language: "chinese",
|
|
analyzer: "jieba",
|
|
query: "信息检索的应用",
|
|
numRows: 1000,
|
|
topK: 5,
|
|
},
|
|
}
|
|
|
|
for _, tc := range testCases {
|
|
t.Run(tc.name, func(t *testing.T) {
|
|
analyzerParams := map[string]any{"tokenizer": tc.analyzer}
|
|
fieldsOption := hp.TNewFieldsOption().TWithAnalyzerParams(analyzerParams)
|
|
function := hp.TNewBM25Function(common.DefaultTextFieldName, common.DefaultTextSparseVecFieldName)
|
|
schemaOption := hp.TNewSchemaOption().TWithFunction(function).TWithEnableDynamicField(true)
|
|
prepare, schema := hp.CollPrepare.CreateCollection(ctx, t, mc, hp.NewCreateCollectionParams(hp.FullTextSearch), fieldsOption, schemaOption)
|
|
insertOption := hp.TNewDataOption().TWithTextLang(tc.language).TWithNb(tc.numRows)
|
|
prepare.InsertData(ctx, t, mc, hp.NewInsertParams(schema), insertOption)
|
|
prepare.FlushData(ctx, t, mc, schema.CollectionName)
|
|
|
|
indexparams := hp.TNewIndexParams(schema).TWithFieldIndex(map[string]index.Index{common.DefaultTextSparseVecFieldName: index.NewSparseInvertedIndex(entity.BM25, 0.1)})
|
|
prepare.CreateIndex(ctx, t, mc, indexparams)
|
|
prepare.Load(ctx, t, mc, hp.NewLoadParams(schema.CollectionName))
|
|
|
|
// search
|
|
queries := []string{tc.query}
|
|
vectors := make([]entity.Vector, 0, len(queries))
|
|
for _, query := range queries {
|
|
vectors = append(vectors, entity.Text(query))
|
|
}
|
|
resSearch, err := mc.Search(ctx, milvusclient.NewSearchOption(schema.CollectionName, tc.topK, vectors).WithConsistencyLevel(entity.ClStrong))
|
|
common.CheckErr(t, err, true)
|
|
common.CheckSearchResult(t, resSearch, len(queries), tc.topK)
|
|
})
|
|
}
|
|
}
|
|
|
|
// TestSearchFullTextWithPartitionKey tests full text search with partition key
|
|
func TestSearchFullTextWithPartitionKey(t *testing.T) {
|
|
ctx := hp.CreateContext(t, time.Second*common.DefaultTimeout)
|
|
mc := hp.CreateDefaultMilvusClient(ctx, t)
|
|
|
|
// Test cases for different languages and analyzers
|
|
testCases := []struct {
|
|
name string
|
|
language string
|
|
analyzer string
|
|
query string
|
|
numRows int
|
|
topK int
|
|
}{
|
|
{
|
|
name: "English_Standard",
|
|
language: "english",
|
|
analyzer: "standard",
|
|
query: "what is information retrieval and its applications?",
|
|
numRows: 1000,
|
|
topK: 5,
|
|
},
|
|
{
|
|
name: "Chinese_Jieba",
|
|
language: "chinese",
|
|
analyzer: "jieba",
|
|
query: "信息检索的应用",
|
|
numRows: 1000,
|
|
topK: 5,
|
|
},
|
|
}
|
|
|
|
for _, tc := range testCases {
|
|
t.Run(tc.name, func(t *testing.T) {
|
|
analyzerParams := map[string]any{"tokenizer": tc.analyzer}
|
|
fieldsOption := hp.TNewFieldOptions().WithFieldOption(common.DefaultTextFieldName, hp.TNewFieldsOption().TWithIsPartitionKey(true).TWithAnalyzerParams(analyzerParams))
|
|
function := hp.TNewBM25Function(common.DefaultTextFieldName, common.DefaultTextSparseVecFieldName)
|
|
schemaOption := hp.TNewSchemaOption().TWithFunction(function)
|
|
prepare, schema := hp.CollPrepare.CreateCollection(ctx, t, mc, hp.NewCreateCollectionParams(hp.FullTextSearch), fieldsOption, schemaOption)
|
|
insertOption := hp.TNewDataOption().TWithTextLang(tc.language).TWithNb(tc.numRows)
|
|
prepare.InsertData(ctx, t, mc, hp.NewInsertParams(schema), insertOption)
|
|
prepare.FlushData(ctx, t, mc, schema.CollectionName)
|
|
|
|
indexparams := hp.TNewIndexParams(schema).TWithFieldIndex(map[string]index.Index{common.DefaultTextSparseVecFieldName: index.NewSparseInvertedIndex(entity.BM25, 0.1)})
|
|
prepare.CreateIndex(ctx, t, mc, indexparams)
|
|
prepare.Load(ctx, t, mc, hp.NewLoadParams(schema.CollectionName))
|
|
|
|
// add field
|
|
newField := entity.NewField().WithName(common.DefaultNewField).WithDataType(entity.FieldTypeInt64).WithNullable(true).WithDefaultValueLong(100)
|
|
err := mc.AddCollectionField(ctx, milvusclient.NewAddCollectionFieldOption(schema.CollectionName, newField))
|
|
common.CheckErr(t, err, true)
|
|
|
|
// search
|
|
queries := []string{tc.query}
|
|
vectors := make([]entity.Vector, 0, len(queries))
|
|
for _, query := range queries {
|
|
vectors = append(vectors, entity.Text(query))
|
|
}
|
|
resSearch, err := mc.Search(ctx, milvusclient.NewSearchOption(schema.CollectionName, tc.topK, vectors).WithConsistencyLevel(entity.ClStrong))
|
|
common.CheckErr(t, err, true)
|
|
common.CheckSearchResult(t, resSearch, len(queries), tc.topK)
|
|
|
|
// search with new field filter
|
|
resSearch, err = mc.Search(ctx, milvusclient.NewSearchOption(schema.CollectionName, tc.topK, vectors).WithConsistencyLevel(entity.ClStrong).
|
|
WithFilter(fmt.Sprintf("%s == 100", common.DefaultNewField)))
|
|
common.CheckErr(t, err, true)
|
|
common.CheckSearchResult(t, resSearch, len(queries), tc.topK)
|
|
})
|
|
}
|
|
}
|
|
|
|
// TestSearchFullTextWithEmptyData tests full text search with empty data
|
|
func TestSearchFullTextWithEmptyData(t *testing.T) {
|
|
ctx := hp.CreateContext(t, time.Second*common.DefaultTimeout)
|
|
mc := hp.CreateDefaultMilvusClient(ctx, t)
|
|
|
|
// Test cases for different empty percent
|
|
testCases := []struct {
|
|
name string
|
|
language string
|
|
analyzer string
|
|
query string
|
|
numRows int
|
|
topK int
|
|
emptyPercent int
|
|
}{
|
|
{
|
|
name: "English_Standard",
|
|
language: "english",
|
|
analyzer: "standard",
|
|
query: "what is information retrieval and its applications?",
|
|
numRows: 3000,
|
|
topK: 5,
|
|
emptyPercent: 90,
|
|
},
|
|
{
|
|
name: "Chinese_Jieba",
|
|
language: "chinese",
|
|
analyzer: "jieba",
|
|
query: "信息检索的应用",
|
|
numRows: 3000,
|
|
topK: 5,
|
|
emptyPercent: 90,
|
|
},
|
|
}
|
|
|
|
for _, tc := range testCases {
|
|
t.Run(tc.name, func(t *testing.T) {
|
|
analyzerParams := map[string]any{"tokenizer": tc.analyzer}
|
|
fieldsOption := hp.TNewFieldOptions().WithFieldOption(common.DefaultTextFieldName, hp.TNewFieldsOption().TWithIsPartitionKey(true).TWithAnalyzerParams(analyzerParams))
|
|
function := hp.TNewBM25Function(common.DefaultTextFieldName, common.DefaultTextSparseVecFieldName)
|
|
schemaOption := hp.TNewSchemaOption().TWithFunction(function)
|
|
prepare, schema := hp.CollPrepare.CreateCollection(ctx, t, mc, hp.NewCreateCollectionParams(hp.FullTextSearch), fieldsOption, schemaOption)
|
|
insertOption := hp.TNewDataOption().TWithTextLang(tc.language).TWithNb(tc.numRows).TWithTextEmptyPercent(tc.emptyPercent)
|
|
prepare.InsertData(ctx, t, mc, hp.NewInsertParams(schema), insertOption)
|
|
prepare.FlushData(ctx, t, mc, schema.CollectionName)
|
|
|
|
indexparams := hp.TNewIndexParams(schema).TWithFieldIndex(map[string]index.Index{common.DefaultTextSparseVecFieldName: index.NewSparseInvertedIndex(entity.BM25, 0.1)})
|
|
prepare.CreateIndex(ctx, t, mc, indexparams)
|
|
prepare.Load(ctx, t, mc, hp.NewLoadParams(schema.CollectionName))
|
|
|
|
// search
|
|
queries := []string{tc.query}
|
|
vectors := make([]entity.Vector, 0, len(queries))
|
|
for _, query := range queries {
|
|
vectors = append(vectors, entity.Text(query))
|
|
}
|
|
resSearch, err := mc.Search(ctx, milvusclient.NewSearchOption(schema.CollectionName, tc.topK, vectors).WithConsistencyLevel(entity.ClStrong))
|
|
common.CheckErr(t, err, true)
|
|
common.CheckSearchResult(t, resSearch, len(queries), tc.topK)
|
|
})
|
|
}
|
|
}
|
|
|
|
// test full-text-search with default text, output text
|
|
func TestFullTextSearchDefaultValue(t *testing.T) {
|
|
ctx := hp.CreateContext(t, time.Second*common.DefaultTimeout)
|
|
mc := hp.CreateDefaultMilvusClient(ctx, t)
|
|
|
|
// create -> insert -> flush -> index -> load
|
|
defaultText := "data mining supports query expansion"
|
|
analyzerParams := map[string]any{"tokenizer": "standard"}
|
|
fieldsOption := hp.TNewFieldOptions().WithFieldOption(common.DefaultTextFieldName, hp.TNewFieldsOption().TWithDefaultValue(defaultText).TWithEnableAnalyzer(true).TWithAnalyzerParams(analyzerParams))
|
|
function := hp.TNewBM25Function(common.DefaultTextFieldName, common.DefaultTextSparseVecFieldName)
|
|
prepare, schema := hp.CollPrepare.CreateCollection(ctx, t, mc, hp.NewCreateCollectionParams(hp.FullTextSearch), fieldsOption, hp.TNewSchemaOption().TWithFunction(function))
|
|
|
|
// insert data with all null
|
|
validData := make([]bool, common.DefaultNb)
|
|
for i := 0; i < common.DefaultNb; i++ {
|
|
validData[i] = false
|
|
}
|
|
insertOption := hp.TNewColumnOptions().WithColumnOption(common.DefaultTextFieldName, hp.TNewDataOption().TWithTextLang(common.DefaultTextLang).TWithValidData(validData))
|
|
prepare.InsertData(ctx, t, mc, hp.NewInsertParams(schema), insertOption)
|
|
prepare.FlushData(ctx, t, mc, schema.CollectionName)
|
|
|
|
indexParams := hp.TNewIndexParams(schema).TWithFieldIndex(map[string]index.Index{common.DefaultTextSparseVecFieldName: index.NewSparseInvertedIndex(entity.BM25, 0.1)})
|
|
prepare.CreateIndex(ctx, t, mc, indexParams)
|
|
prepare.Load(ctx, t, mc, hp.NewLoadParams(schema.CollectionName))
|
|
|
|
// full text search
|
|
vectors := make([]entity.Vector, 0, common.DefaultNq)
|
|
for i := 0; i < common.DefaultNq; i++ {
|
|
vectors = append(vectors, entity.Text(defaultText))
|
|
}
|
|
|
|
resSearch, err := mc.Search(ctx, milvusclient.NewSearchOption(schema.CollectionName, common.DefaultLimit, vectors).WithConsistencyLevel(entity.ClStrong).WithOutputFields(common.DefaultTextFieldName))
|
|
common.CheckErr(t, err, true)
|
|
common.CheckSearchResult(t, resSearch, common.DefaultNq, common.DefaultLimit)
|
|
common.CheckOutputFields(t, []string{common.DefaultTextFieldName}, resSearch[0].Fields)
|
|
for _, field := range resSearch[0].Fields {
|
|
if field.Name() == common.DefaultTextFieldName {
|
|
for i := 0; i < field.Len(); i++ {
|
|
fieldData, _ := field.GetAsString(i)
|
|
require.EqualValues(t, defaultText, fieldData)
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
// TestTextMatchMinimumShouldMatch verifies text_match(..., minimum_should_match=N)
|
|
func TestTextMatchMinimumShouldMatch(t *testing.T) {
|
|
ctx := hp.CreateContext(t, time.Second*common.DefaultTimeout)
|
|
mc := hp.CreateDefaultMilvusClient(ctx, t)
|
|
|
|
function := hp.TNewBM25Function(common.DefaultTextFieldName, common.DefaultTextSparseVecFieldName)
|
|
// Provide valid field options instead of nil to satisfy CreateCollection's type check
|
|
analyzerParams := map[string]any{"tokenizer": "standard"}
|
|
fieldsOption := hp.TNewFieldsOption().TWithAnalyzerParams(analyzerParams)
|
|
prepare, schema := hp.CollPrepare.CreateCollection(ctx, t, mc, hp.NewCreateCollectionParams(hp.FullTextSearch), fieldsOption, hp.TNewSchemaOption().TWithFunction(function))
|
|
|
|
docs := []string{"a b", "a c", "b c", "c", "a b c"}
|
|
insertOption := hp.TNewDataOption().TWithTextLang(common.DefaultTextLang).TWithTextData(docs)
|
|
prepare.InsertData(ctx, t, mc, hp.NewInsertParams(schema), insertOption)
|
|
prepare.FlushData(ctx, t, mc, schema.CollectionName)
|
|
|
|
indexparams := hp.TNewIndexParams(schema).TWithFieldIndex(map[string]index.Index{common.DefaultTextSparseVecFieldName: index.NewSparseInvertedIndex(entity.BM25, 0.1)})
|
|
prepare.CreateIndex(ctx, t, mc, indexparams)
|
|
prepare.Load(ctx, t, mc, hp.NewLoadParams(schema.CollectionName))
|
|
|
|
// min=1 should return docs containing any token from "a b c"
|
|
expr1 := fmt.Sprintf("text_match(%s, \"%s\", minimum_should_match=%d)", common.DefaultTextFieldName, "a b c", 1)
|
|
res1, err := mc.Query(ctx, milvusclient.NewQueryOption(schema.CollectionName).WithFilter(expr1))
|
|
require.NoError(t, err)
|
|
require.GreaterOrEqual(t, res1.ResultCount, 4)
|
|
|
|
// min=3 should return only the doc containing all three tokens
|
|
expr3 := fmt.Sprintf("text_match(%s, \"%s\", minimum_should_match=%d)", common.DefaultTextFieldName, "a b c", 3)
|
|
res3, err := mc.Query(ctx, milvusclient.NewQueryOption(schema.CollectionName).WithFilter(expr3))
|
|
require.NoError(t, err)
|
|
require.GreaterOrEqual(t, res3.ResultCount, 1)
|
|
|
|
// min large (e.g. 10) should return 0
|
|
exprLarge := fmt.Sprintf("text_match(%s, \"%s\", minimum_should_match=%d)", common.DefaultTextFieldName, "a b c", 10)
|
|
resLarge, err := mc.Query(ctx, milvusclient.NewQueryOption(schema.CollectionName).WithFilter(exprLarge))
|
|
require.NoError(t, err)
|
|
require.Equal(t, 0, resLarge.ResultCount)
|
|
}
|